Gamified Adaptive Approach Bias Modification in Individuals With Methamphetamine Use History From Communities in Sichuan: Pilot Randomized Controlled Trial
Bibliographic record
Abstract
Background: Cognitive bias modification (CBM) programs have shown promise in treating psychiatric conditions, but they can be perceived as boring and repetitive. Incorporating gamified designs and adaptive algorithms in CBM training may address this issue and enhance engagement and effectiveness. objectives: This study aims to gather preliminary data and assess the preliminary efficacy of an adaptive approach bias modification (A-ApBM) paradigm in reducing cue-induced craving in individuals with methamphetamine use history. Methods: A randomized controlled trial with 3 arms was conducted. Individuals aged 18-60 years with methamphetamine dependence and at least 1 year of methamphetamine use were recruited from 12 community-based rehabilitation centers in Sichuan, China. Individuals with the inability to fluently operate a smartphone and the presence of mental health conditions other than methamphetamine use disorder were excluded. The A-ApBM group engaged in ApBM training using a smartphone app for 4 weeks. The A-ApBM used an adaptive algorithm to dynamically adjust the difficulty level based on individual performance. Cue-induced craving scores and relapses were assessed using a visual analogue scale at baseline, postintervention, and at week-16 follow-up. Results: A total of 136 participants were recruited and randomized: 48 were randomized to the A-ApBM group, 48 were randomized to the static approach bias modification (S-ApBM) group, and 40 were randomized to the no-intervention control group. The A-ApBM group showed a significant reduction in cue-induced craving scores at postintervention compared with baseline (Cohen d=0.34; P<.01; 95% CI 0.03-0.54). The reduction remained significant at the week-16 follow-up (Cohen d=0.40; P=.01; 95% CI 0.18-0.57). No significant changes were observed in the S-ApBM and control groups. Conclusions: The A-ApBM paradigm with gamified designs and dynamic difficulty adjustments may be an effective intervention for reducing cue-induced craving in individuals with methamphetamine use history. This approach improves engagement and personalization, potentially enhancing the effectiveness of CBM programs. Further research is needed to validate these findings and explore the application of A-ApBM in other psychiatric conditions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".